Tin

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Recurrent Neural Networks (RNNs) continue to show outstanding performance in sequence modeling tasks. However, training RNNs on long sequences often face challenges like slow inference, vanishing gradients and difficulty in capturing long term dependencies. In backpropagation through time settings, …

See the first in a three part series that explains machine learning through math.<p>Over the last few years, we've heard a lot about neural networks, whether its Google's Deep Dream software creating horrifying digital dreamscapes or composites of pop songs written by a machine. But how do these …

In 2006, Fei-Fei Li started ruminating on an idea.<p>Li, a newly-minted computer science professor at University of Illinois Urbana-Champaign, saw her colleagues across academia and the AI industry hammering away at the same concept: a better algorithm would make better decisions, regardless of the …